Exergy, exergoeconomic and multi-objective optimization of a clean hydrogen and electricity production using geothermal-driven energy systems
Cao Y. Dhahad H.A. Togun H. Hussen H.M. Anqi A.E. Farouk N. Issakhov A.
22 July 2022Elsevier Ltd
International Journal of Hydrogen Energy
2022#47Issue 6225964 - 25983 pp.
In this research paper, comprehensive thermodynamic modeling of an integrated energy system consisting of a multi-effect desalination system, geothermal energy system, and hydrogen production unit is considered and the system performance is investigated. The systems primary fuel is a geothermal two-phase flow. The system consists of a single flash steam-based power system, ORC, double effect water–lithium bromide absorption cooling system, PEM electrolyzer, and MED with six effects. The effect of numerous design parameters such as geothermal temperature and pressure on the net power of steam turbine and ORC cycle, the cooling capacity of an absorption chiller, the amount of produced hydrogen in PEM electrolyzer, the mass flow rate of distillate water from MED and the total cost rate of the system are studied. The simulation is carried out by both EES and Matlab software. The results indicate the key role of geothermal temperature and show that both total exergy efficiency and total cost rate of the system elevate with increasing geothermal temperature. Also, the impact of changing absorption chiller parameters like evaporator and absorber temperatures on the COP and GOR of the system is investigated. Since some of these parameters have various effects on cost and efficiency as objective functions, a multi-objective optimization is applied based on a Genetic algorithm for this system and a Pareto-Frontier diagram is presented. The results show that geothermal main temperature has a significant effect on both system exergy efficiency and cost of the system. An increase in this temperature from 260 C to 300 C can increase the exergy efficiency of the system for an average of 12% at various working pressure and also increase the cost of the system by 13%.
Exergoeconomic analysis , Genetic algorithm , Integrated MED system , Multi-objective optimization
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School of Mechatronic Engineering, Xian Technological University, Xian, 710021, China
Mechanical Engineering Department, University of Technology, Baghdad, Iraq
Department of Biomedical Engineering, University of Thi-Qar, Nassiriya, 64001, Iraq
Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia
Mechanical Engineering Department, College of Engineering, Prince Sattam Bin Abdulaziz University, Alkharj, 16273, Saudi Arabia
Mechanical Engineering Department, Faculty of Engineering, Red Sea University Port Sudan, Sudan
Department of Mathematical and Computer Modelling, Al-Farabi Kazakh National University, Almaty, 050040, Kazakhstan
Department of Mathematics and Cybernetics, Kazakh British Technical University, Almaty, 050000, Kazakhstan
School of Mechatronic Engineering
Mechanical Engineering Department
Department of Biomedical Engineering
Department of Mechanical Engineering
Mechanical Engineering Department
Mechanical Engineering Department
Department of Mathematical and Computer Modelling
Department of Mathematics and Cybernetics
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